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US12372679B2ActiveUtilityPatentIndex 50

Utility pole localization by distributed fiber sensing of aerial fiber cable

Assignee: NEC LAB AMERICA INCPriority: Oct 19, 2020Filed: Oct 18, 2021Granted: Jul 29, 2025
Est. expiryOct 19, 2040(~14.3 yrs left)· nominal 20-yr term from priority
Inventors:TIAN YUEHAN SHAOBOOZHARAR SARPERDING YANGMINLU YOU
G06N 3/0464G01H 1/006G01H 9/004G01N 29/2418G01H 9/00G01N 2291/0423G01D 5/35361G06N 3/04G01D 5/35358G01V 1/001G01V 1/226
50
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Claims

Abstract

Aspects of the present disclosure describe the localization of a utility pole by distributed fiber sensing of aerial fiber cable suspended from the utility pole.

Claims

exact text as granted — not AI-modified
The invention claimed is: 
     
       1. A method for determining a location of a utility pole, the method comprising:
 receiving, from an aerial optical fiber suspended at least in part by the utility pole, an optical signal containing scattering effects resulting from an instant mechanical impact applied to the utility pole; 
 identifying, based on the received optical signal containing the scattering effects resulting from the instant mechanical impact applied to the utility pole, a first vibration of the aerial optical fiber due to vibration of the utility pole resulting from the instant mechanical impact applied to the utility pole; 
 analyzing, based on the identified first vibration, a location along the length of the optical fiber where the instant mechanical impact applied to the utility pole occurred; and 
 determining, based on the location along the length of the optical fiber where the instant mechanical impact applied to the utility pole occurred, the location of the utility pole. 
 
     
     
       2. The method according to  claim 1 , wherein the received optical signal contains a time of vibrations. 
     
     
       3. The method according to  claim 2 , further comprising:
 plotting, based on the received optical signal, a time the instant mechanical impact applied to the utility pole occurred and a location where the instant mechanical impact occurred. 
 
     
     
       4. The method according to  claim 1 , wherein the identification of the first vibration is performed using edge detection and deep learning methodologies. 
     
     
       5. A system for determining a location of a utility pole, the system comprising:
 a non-transitory computer readable medium configured to store instructions thereon; 
 a DFOS configured to receive from an aerial optical fiber suspended at least in part by the utility pole, an optical signal containing scattering effects resulting from an instant mechanical impact applied to the utility pole, wherein the DFOS connected to the aerial optical fiber; 
 a processor connected to the DFOS and the non-transitory computer readable medium, wherein the processor is configured to execute the instructions for:
 identifying, based on the received optical signal containing the scattering effects resulting from the instant mechanical impact applied to the utility pole, a first vibration of the aerial optical fiber due to vibration of the utility pole resulting from the instant mechanical impact applied to the the utility pole; 
 analyzing, based on the identified first vibration, a location along the length of the optical fiber where the instant mechanical impact applied to the utility pole occurred; 
 determining, based on the location along the length of the optical fiber where the instant mechanical impact applied to the utility pole occurred, the location of the utility pole. 
 
 
     
     
       6. The system according to  claim 5 , wherein the received optical signal contains a time of the vibrations. 
     
     
       7. The system according to  claim 6 , wherein the processor is further configured to execute the instructions for:
 plotting, based on the received optical signal, a time the instant mechanical impact applied to the utility pole occurred and the location where the instant mechanical impact occurred. 
 
     
     
       8. The system according to  claim 5 , wherein the identification of the first vibration is performed using edge detection and deep learning methodologies.

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